10 June 2021, DIEP Seminars, Casper van Elteren

Understanding dynamical systems is a fundamental problem for the 21st century. Despite the prima facie differences and purposes of many real-world networks, previous research shows several universal characteristics in networks properties such as the small-world phenomenon, fat-tail degree and feedback loops. This has led to the common but often implicit assumption that the connectedness of a node in the network is proportional to its dynamic importance. For example in epidemic research, high degree nodes or "super-spreaders" are associated to dominant epidemic risk and therefore deserve special attention. Yet prior research shows that the shared universality in network characteristics is not shared in the dynamic or functional properties of many real-world systems.

In this talk I will explore the relation between local interactions and macroscopic properties of a system through the lens of statistical physics and information theory. In particular, I will show novel methods on determining the so-called driver node in complex systems, and how tipping points can be studied from an information theoretical perspective. (website + slides: https://cvanelteren.github.io/talk/diep2021/)